Results 51 to 60 of about 349,441 (269)

Visual Perception for a Partner Robot Based on Computational Intelligent [PDF]

, 2005
We propose computational intelligence for partner robot perception in which the robot requires the capability of visual perception to interact with human beings.
Kubota, Naoyuki, Sulistijono, Indra Adji
core  

Robust and Real-time Deep Tracking Via Multi-Scale Domain Adaptation

, 2017
Visual tracking is a fundamental problem in computer vision. Recently, some deep-learning-based tracking algorithms have been achieving record-breaking performances. However, due to the high complexity of deep learning, most deep trackers suffer from low
Li, Hanxi, Li, Yi, Porikli, Fatih, Shen, Fumin, Wang, Xinyu   +4 more
core   +1 more source

Hippo pathway at the crossroads of stemness and therapeutic resistance in breast cancer

Molecular Oncology, EarlyView.
Dysregulation of the Hippo pathway drives nuclear accumulation of YAP/TAZ, activating stemness‐related transcriptional programs that sustain breast cancer stemness and fuel therapeutic resistance across subtypes, underscoring Hippo signaling as a targetable vulnerability. Figure created and edited with BioRender.com.
Giulia Schiavoni, Antonella Palmese, Stefano Scalera, Laura Cipriani, Davide Mascolo, Patrizia Vici, Teresa Arcuri, Lorena Filomeno, Eriseld Krasniqi, Giovanni Blandino, Giulia Bon, Marcello Maugeri‐Saccà   +11 more
wiley   +1 more source

Query-Based Object Visual Tracking with Parallel Sequence Generation

Sensors
Query decoders have been shown to achieve good performance in object detection. However, they suffer from insufficient object tracking performance. Sequence-to-sequence learning in this context has recently been explored, with the idea of describing a ...
Chang Liu, Bin Zhang, Chunjuan Bo, Dong Wang   +3 more
doaj   +1 more source

Online Multi-Object Tracking With Visual and Radar Features

IEEE Access, 2020
Multi-object tracking (MOT) constructs multiple object trajectories by associating detections between consecutive frames while maintaining object identities.
Seung-Hwan Bae
doaj   +1 more source

Recurrent Filter Learning for Visual Tracking

, 2017
Recently using convolutional neural networks (CNNs) has gained popularity in visual tracking, due to its robust feature representation of images. Recent methods perform online tracking by fine-tuning a pre-trained CNN model to the specific target object ...
Chan, Antoni B., Yang, Tianyu
core   +1 more source

Explicit Visual Prompts for Visual Object Tracking

Proceedings of the AAAI Conference on Artificial Intelligence
How to effectively exploit spatio-temporal information is crucial to capture target appearance changes in visual tracking. However, most deep learning-based trackers mainly focus on designing a complicated appearance model or template updating strategy, while lacking the exploitation of context between consecutive frames and thus entailing the when-and-
Liangtao Shi, Bineng Zhong, Qihua Liang, Ning Li 0044, Shengping Zhang, Xianxian Li   +5 more
openaire   +2 more sources

NKCC1: A key regulator of glioblastoma progression

Molecular Oncology, EarlyView.
Glioblastoma (GBM) progression is driven by disrupted chloride cotransporter homeostasis. NKCC1 is highly expressed in stem‐like, astrocytic, and progenitor cells, correlating with earlier recurrence, while overall survival remains unaffected. NKCC1 serves as a prognostic marker and potential therapeutic target, linking chloride transporter imbalance ...
Anja Thomsen, Diana Freitag, Madlen Haase, Christian Senft, Falko Schwarz, Silke Keiner   +5 more
wiley   +1 more source

Integration of the 3D Environment for UAV Onboard Visual Object Tracking

Applied Sciences, 2020
Single visual object tracking from an unmanned aerial vehicle (UAV) poses fundamental challenges such as object occlusion, small-scale objects, background clutter, and abrupt camera motion.
Stéphane Vujasinović, Stefan Becker, Timo Breuer, Sebastian Bullinger, Norbert Scherer-Negenborn, Michael Arens   +5 more
doaj   +1 more source

Improving Visual Object Tracking through Visual Prompting

IEEE Transactions on Multimedia
Learning a discriminative model that distinguishes the specified target from surrounding distractors across frames is essential for generic object tracking (GOT). Dynamic adaptation of target representation against distractors remains challenging because prevailing trackers exhibit limited discriminative capability.
Shih-Fang Chen, Jun-Cheng Chen, I-Hong Jhuo, Yen-Yu Lin   +3 more
openaire   +2 more sources